Detection of Iberian terrestrial mammals employing olfactory, visual and auditory attractants

Suárez-Tangil, Bruno D.; Rodrı́guez, Alejandro

doi:10.1007/s10344-017-1150-1

Cited by 12 publications

(16 citation statements)

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“…For the lure treatment, we used a white 2.5‐cm plaster disk saturated with a synthetic fatty acid scent (Predator Survey disks; hereafter, FAS [USDA Wildlife Services, Pocatello, ID, USA]). Fatty acid scent disks are a commonly used olfactory lure suggested to increase the detectability of mesocarnivores, especially coyote (Roughton and Sweeny 1982, Suárez‐Tangil and Rodríguez 2017). The non‐lure control was a piece of white cardstock cut to an identical size to that of the FAS disk.…”

Section: Methodsmentioning

confidence: 99%

“…Studies that have quantified the effect of lure or bait typically compare detection probability across independent locations where lure is either present or absent from the view of a camera trap (Garrote et al 2012, Bischof et al 2014, du Preez et al 2014, Rocha et al 2016, Suárez‐Tangil and Rodríguez 2017). However, with this type of study design, it is difficult to separate the effect of lure from other factors that influence detectability, such as species abundance (McCarthy et al 2013) and local habitat conditions.…”

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confidence: 99%

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Effect of Lure on Detecting Mammals with Camera Traps

Fidino

Barnas

Lehrer

et al. 2020

Wildlife Society Bulletin

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Motion-triggered camera traps are subject to imperfect detection and thus camera-trapping surveys often try to increase species detectability as part of the study design. One possible way to increase detectability is to use lures, which may encourage a species to investigate a given area. Yet the effectiveness of lures is primarily grounded in anecdotal support. We quantified the effect of a common olfactory carnivore lure on the detectability of mammals near Chicago, Illinois, USA, during 27 August 2018-25 September 2018. We deployed 2 camera traps per site, spaced apart by 100 m, to assess whether lure can modify detectability both within and between sites. At each camera location, we changed lure treatments every 7 days and placed either a lure or a non-lure control in view of each camera following a fully crossed design. For analysis, we developed single-season occupancy models with 3 distinct observational models to quantify whether lure increased the number of days a species was detected, decreased the amount of time to first detection, and increased the number of images collected. Lure induced a subtle change in detectability. Virginia opossum (Didelphis virginiana) responded most to the presence of lure; their daily detection probability rose by roughly 5% and the number of opossum images nearly doubled. However, the effect of lure was often negative for prey species. When lure was present, eastern cottontail (Sylvilagus floridanus) daily detection probability decreased by 5% and they were photographed 63% less often. Likewise, eastern gray squirrel (Sciurus carolinensis) arrived 70% later to a camera trap if lure was present and were photographed 14% less. By using multiple criteria, we were able to better understand how wildlife respond to lure while camera-trapping more thoroughly than would be possible with a single metric. Our results show that lure may not be as effective as expected in terms of increasing detectability, but the choice to use lure should depend on several factors, including the density of the study species, species life history, and the dynamics between the species studied.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Effect of Lure on Detecting Mammals with Camera Traps

Fidino

Barnas

Lehrer

et al. 2020

Wildlife Society Bulletin

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“…First, as in all occupancy frameworks, we assume that detection probability ( p ) of our sampling device is either constant, or all sources of heterogeneity in p are controlled or explicitly modeled (MacKenzie et al 2017). For camera traps, an increasingly large list of local site factors has been shown to influence p , many of which impact (1) the ability to predict or funnel animal movement to the camera (e.g., placement on/off trails, Cusack et al 2015, Kolowski and Forrester 2017; roads, Sollmann et al 2013, Mann et al 2015; presence of logs, Kolowski and Forrester 2017), (2) the ability to physically detect or see the focal species (e.g., vegetation density, Hofmeester et al 2017, Kolowski and Forrester 2017; camera detection distance, Hofmeester et al 2017), or (3) the general favorability of the local site for the species of interest (e.g., local resource availability, Brassine and Parker 2015; presence of bait/lure, Satterfield et al 2017, Suarez‐Tangil and Rodriguez 2017). Although efforts have been made to summarize current knowledge about the factors influencing detection probability of a species (Hofmeester et al 2019), the ever‐growing list of potentially important factors should raise doubts as to our ability to identify and measure all the key factors in any given scenario.…”

Section: Introductionmentioning

confidence: 99%

High‐density camera trap grid reveals lack of consistency in detection and capture rates across space and time

2021

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Counts of independent photo events from camera traps are commonly used to make inference about species occupancy, the density of unmarked populations, and the relative abundance of species across time and space. These applications rest on the untested assumption that data collected from individual cameras are representative of the landscape location in which they are placed, and that nearby cameras would record similar data when any additional micro‐site differences are accounted for. We established a high‐density camera trapping grid (100 × 100 m; 27 cameras) in Virginia, USA, to explicitly test these assumptions, investigating variation in capture rates and detection probabilities for a range of terrestrial mammals during four 2‐month seasonal surveys. Despite controlling for numerous habitat and placement factors, we documented, across all 5 focal species, large ranges and coefficients of variation in both capture rate and detection probabilities, which were similar to those seen across 2 sets of independent forest sampling sites from a larger, more typical camera trap sampling design. We also documented a lack of spatial autocorrelation in capture rate at any distance. Measured local covariates relevant to the camera viewshed (stem density, camera height, log presence, effective detection distance [EDD], total dbh of oak trees) rarely explained any significant portion of observed variation in capture rates or detection probabilities across the grid. The influence of EDD, measured here for the first time for individual camera stations, was inconsistently important and varied in direction of effect depending on species and season. Our study indicates single‐camera stations may fail to sample animal presence and frequency of use in a robust and repeatable way, primarily resulting from the influence of both idiosyncrasies in animal movement and measured and unknown micro‐site characteristics. We recommend spatial replication within sites (e.g., small‐scale shifting of cameras or use of multiple stations) should be considered to minimize impacts of relevant micro‐site characteristics, some of which may be difficult to identify.

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“…Alternatively, skunk‐based lure, a novel stimulus, may elicit curiosity (Harrington, Harrington & Macdonald, 2009). Other studies have reported little effect of scent lures from sympatric predators on badger attraction (Monterroso et al ., 2011; Suárez‐Tangil & Rodríguez, 2017), possibly indicating a greater role of the novelty and curiosity aspects.…”

Section: Discussionmentioning

confidence: 99%

Sooner, closer, or longer: detectability of mesocarnivores at camera traps

et al. 2020

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Camera trapping, paired with analytical methods for estimating species occurrence, population size or density, can yield information with direct consequences for wildlife management and conservation. Detectability, the ability to detect a species or individual if it is present, affects the reliability and efficiency of camera trap surveys and, in turn, varies across species, space and time. Greater detectability means greater sample size, and a common approach to boost detectability of wildlife by camera traps involves the application of olfactory lures. Using a camera trap study on sympatric mesocarnivores (European badger Meles meles, red fox Vulpes vulpes, pine marten Martes martes and domestic cat Felis catus), we quantified three elements of detectability: (1) the time until first detection ('sooner', conditional on being present), (2) the proximity to a focal point in front of the camera ('closer', conditional on being detected) and (3) the duration of exposure to the camera ('longer', conditional on being detected). A hierarchical analytical approach and a quasi-experimental setup allowed us to test for and quantify the species-specific effect of olfactory lures on these aspects of detectability. Depending on species, average median time to first detection ranged from 4 to 28 days, distance to the focal point from 0.3 to 0.8 body lengths, and median time to departure from 2 to 6 seconds. Credible intervals overlapped substantially between most species in all three measures, and variation between observations was extensive. We detected effects of lures on time to first detection for cats (castoreum; American beaver Castor canadensis scent), distance to focal point for badgers (striped skunk Mephitis mephitis scent) and martens (castoreum, fox and skunk scents), and the duration of exposure for foxes (fox and skunk scents). We discuss how a multifaceted perspective on detectability in camera trap studies, linked with species biology, can give investigators a more structured approach to selecting and testing measures intended to boost detection probability.

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Detection of Iberian terrestrial mammals employing olfactory, visual and auditory attractants

Cited by 12 publications

References 50 publications

Effect of Lure on Detecting Mammals with Camera Traps

Effect of Lure on Detecting Mammals with Camera Traps

High‐density camera trap grid reveals lack of consistency in detection and capture rates across space and time

Sooner, closer, or longer: detectability of mesocarnivores at camera traps

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